. *we improved the goodness
of fit by 35K on 3 additional degrees of freedom. In other words, we need the
additional 3 terms to fit the data, but this model does not yet fit the data
well

. predict
P_endogamy_full

(option
n assumed; predicted number of events)

. table
hed wed, contents(sum count sum P_endogamy_full) row col

------------------------------------------------------------

husband's
|
wife's
education

education | <HS
HS Some Col
BA+ Total

----------+-------------------------------------------------

<HS | 32016
33374 8407
988 74785

| 32016 22561.17
15875.39 4332.443 74785

|

HS | 28370 137876
43783 8446 218475

| 17790.29 137876 49342.89
13465.83 218475

|

Some Col
| 7051
48766 61633
18195 135645

| 12987.8 51193.47
61633 9830.73 135645

|

BA+ | 984
13794 28635
51224 94637

| 5626.913 22179.36
15606.73 51224 94637

|

Total
| 68421 233810
142458 78853 523542

| 68421 233810
142458 78853 523542

------------------------------------------------------------

. *The independence model
implies that education does not matter at all in mate selection, i.e. that mate
selection occurs independent of the education of the
spouse. That seems to be not true at all.

. * The second model,
simple endogamy, implies that there is a uniform force of endogamy and everyone
else marries without regard to education. This fit better but still not well
enough.

. * This last model assumes
that the force of educational endogamy varies across educational groups, which
seems to be true, but this model still makes no assumptions about what happens
away from the educational endogamy diagonal, so the fit here is still not so
good.

. *The next thing to add
into the model is some kind of allowance for the lack of marriages where the
educational attainments are most unequal.

. *One last thing to look
at is ways of testing whether two coefficients are significantly different from
each other.

. test
_x_8--_x_9=0

( 1)
[count]_x_8 + [count]_x_9 = 0

chi2( 1) =28496.82

Prob > chi2 = 0.0000

. *the answer is up to this
point, the two middle categories of educational endogamy are still
significantly different, but as we add other terms into the model, this difference
will dissipate, and we will end up saving 1df by combining them.

* Take a look at my excel
file for a summary of this analysis.

. * if
you have made changes to the dataset, remember to save before quitting